Maternal and perinatal outcomes in obese parturients with epidural analgesia: a systematic review
Bibliographic record
Abstract
OBJECTIVES: Obesity in pregnancy is associated with several risks during vaginal delivery. Several guidelines advise early epidural placement. This systematic review summarizes evidence on the maternal and perinatal outcome of epidural analgesia (EA) for vaginal delivery in obese women. METHODS: A systematic literature search was conducted to identify studies reporting EA during vaginal delivery in obese women. Study information, baseline characteristics, and outcomes were extracted. RESULTS: Eleven studies (31,325 patients total) were included. Newcastle-Ottawa Scale quality scores ranged from 2/8 to 7/8. Studies varied in study group choice, baseline characteristics, and outcome measures. Five studies reported patient-oriented outcomes, nine reported technical outcomes regarding catheter placement. One study compared obese women with early vs. late vs. no EA and reported similar incidence of instrumental deliveries (5.3 vs. 1.8 % vs. 0 %, p=0.315) and similar Apgar scores (8.37 ± 1.17 vs. 8.43 ± 1.28 vs. 8.08 ± 2.02, p=0.519). Other studies used a comparison of obese with non-obese women, both receiving EA. Incidence of instrumental deliveries was similar, but the incidence of cesarean delivery and several other outcomes was increased in obese women. CONCLUSIONS: The selected literature predominantly reports on technical difficulties regarding EA. In many studies but one, we found a sub-optimal comparison of obese and non-obese women with EA. Side effects of EA in obese women are suggested in some studies, but we believe that the true influence of EA in obese parturients is insufficiently reported. To fully understand associated risks and benefits for these women, this population should be studied separately, and more evidence is needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".